The COVID-19 pandemic has created an unprecedented surge in demand for healthcare and consumer products. This crisis has demanded stockpiles of supplies and has shifted the supply chain to local production.
It seems that everyone is interested in noncontact gaging these days. Laser scanners, structured light, confocal chromatic sensors, and CCD cameras have all made significant advances in the last decade, leaving us to wonder if this century old technology is still useful today.
Existing models and quality characteristics used for software, systems, and data quality can be leveraged to identify cost categories and support the creation of a Cost of Quality System for Quality 4.0.
As the immediate threat of Covid-19 subsides, companies are creating plans for introducing safe working practices. When it comes to sharing equipment, especially microscopes, there are concerns regarding cross-contamination and effective cleaning because most of the time an operator’s eyes come in direct contact with microscope eyepieces.
In 1969, I had a microphone perched next to the radio, prepared to record each Beatles song played, just to satisfy my obsession at the time. What resulted on my old reel-to-reel player was a series of songs missing the first five seconds of each.
More important than the inventor, the first company to market, or even the technology itself, is adoption of the technology. Whether a technology is adopted early or late can make or break not only the technology, inventor, company, or entire industry, but also an entire economy.
In a recent gathering of quality professionals, the subject of unsuccessful change implementation surfaced. Most people understand change is necessary for survival, but in this era it is happening at an unprecedented, almost vertical rate. The bottom line though is that change is uncomfortable for most and it is common for people to resist change.
You’ve learned about light sources, lenses, cameras, camera interfaces, and image processing software. Now, you may be wondering exactly how to design and implement a complete, successful machine vision system.
Over the past decade manufacturers have increasingly turned to flexible, customizable automation platforms to meet the demands of high mix/low volume orders and ensure their long-term survival in a competitive manufacturing environment.
In the world of machine vision, as in any tech field, there is a distinct divide between hardware and software. The hardware includes components of machine imaging systems such as the physical camera, lensing, cable interfaces, the PC or processor, etc. and are defined by rigid specifications (i.e. resolution of a camera, processing power, bandwidth of interface).